Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/el-feo/ai-context/qa-creategit clone --depth 1 https://github.com/el-feo/ai-contextWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00012 | $0.01947 |
| Opus 5 | $0.00006 | $0.00974 |
| Sonnet 5 | $0.00002 | $0.00389 |
| Haiku 4.5 | $0.00001 | $0.00195 |
Grade A, and why
qa-create scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 303 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resolution order if omitted:
- Most recent open issue labeled
PRD:gh issue list -l PRD -s open --limit 1 --json number -q '.[0].number'
<usage_examples> With PRD number:
/ghpm:qa-create prd=#42
Auto-resolve most recent PRD:
/ghpm:qa-create
</usage_examples>
<qa_issue_template>
QA Issue Body Template
# QA: <PRD Title> - Acceptance Testing
## Overview
<Brief description derived from PRD objective>
## Parent PRD
- PRD: #<PRD_NUMBER>
## QA Steps
(Populated by /ghpm:qa-create-steps)
- [ ] (No steps created yet)
## Status
- [ ] All steps created
- [ ] All steps passed
- [ ] Bugs found: (none)
</qa_issue_template>
Step 1: Resolve PRD Number
# If prd=#N is provided, use N
PRD={provided_prd_number}
# Else: auto-resolve to most recent open PRD
PRD=$(gh issue list -l PRD -s open --limit 1 --json number -q '.[0].number')
if [ -z "$PRD" ]; then
echo "Error: No open PRD found. Specify prd=#N or create a PRD first."
exit 1
fi
# Validate PRD number is positive integer
if ! [[ "$PRD" =~ ^[0-9]+$ ]]; then
echo "Error: Invalid PRD number. Use format: prd=#123"
exit 1
fi
Step 2: Fetch PRD Details
# Fetch PRD title, body, and URL
PRD_DATA=$(gh issue view "$PRD" --json title,body,url -q '.')
PRD_TITLE=$(echo "$PRD_DATA" | jq -r '.title')
PRD_URL=$(echo "$PRD_DATA" | jq -r '.url')
if [ -z "$PRD_TITLE" ]; then
echo "Error: Could not fetch PRD #$PRD. Check if it exists and is accessible."
exit 1
fi
echo "PRD #$PRD: $PRD_TITLE"
echo "URL: $PRD_URL"
Step 3: Ensure QA Label Exists
# Create QA label if it doesn't exist (ignore error if already exists)
gh label create QA --description "QA Issue for acceptance testing" --color 6B3FA0 2>/dev/null || true
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 303 lines · 12 tokens per session scan A 656c5f3e1901
qa-create is a command published in the GitHub repository el-feo/ai-context (12 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 1,947 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.